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A Comparative Study of VaR Estimation for Structured Products
Author(s) -
FenYing Chen
Publication year - 2010
Publication title -
economics research international
Language(s) - English
Resource type - Journals
eISSN - 2090-2123
pISSN - 2090-2131
DOI - 10.1155/2010/838469
Subject(s) - heteroscedasticity , autoregressive conditional heteroskedasticity , econometrics , volatility (finance) , mean squared error , economics , statistics , estimation , mathematics , multivariate statistics , mean absolute error , management
The previous literature commonly concluded that GARCH models provide better volatility forecasts in financial markets. This paper adopts the backtesting criteria, the multivariate extension of the Diebold and Mariano (1995) test, RMSE (root mean squared errors), and MAE (mean absolute errors) to compare the performances of selected conditional heteroscedastic models for structured products in the low oil price and high oil price periods. The results illustrate that, in general, the performance of GARCH type seems to be better in the whole periods whereas it is not in the low period and the high oil price period

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